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The Double-H Maze: A Robust Behavioral Test for Learning and Memory in Rodents
Published on: July 8, 2015
Reward contingency reorganizes lateral orbitofrontal cortex pyramidal neuron activity from reward-aligned to
Zicheng Yang1, Xiaolan Chen1, Xiaohong Sun1
1School of Basic Medical Sciences, Beijing Key Laboratory of Neural Regeneration and Repair, Key Laboratory for Neurodegenerative Diseases of the Ministry of Education, Laboratory for Clinical Medicine, Capital Medical University, Beijing, China.
Background:
Animals must learn not only which cues predict reward, but also when to act to obtain it. Although the orbitofrontal cortex (OFC) encodes reward-related information, whether reward contingency is sufficient to reorganize the temporal alignment of OFC activity remains unclear.
Methods:
We recorded calcium signals from lateral OFC pyramidal neurons (lOFC-PNs) in wild-type (WT) and Sapap3 knockout (KO) mice using fiber photometry, during sequential learning of Pavlovian and instrumental contingencies in a single-odor reward association task. We further used a cue-free lick test and linear mixed-effects modeling to dissociate the contribution of reward contingency from that of licking behavior.
Results:
Licking behavior and lOFC-PN activity were comparable between WT and KO mice, supporting pooled analysis. Under Pavlovian contingencies, licking and lOFC-PN activity were concentrated around reward delivery. Under instrumental contingencies, both shifted to the pre-reward delay period, and the timing of lOFC-PN activity became progressively coupled to anticipatory licking as learning advanced. A cue-free lick test and linear mixed-effects modeling confirmed that these contingency-related differences reflected reward contingency rather than licking per se.
Conclusion:
These findings indicate that reward contingency dynamically reorganizes the temporal alignment of lOFC-PN activity and its coupling with behavior, shifting from reward-aligned under Pavlovian learning to action-aligned under instrumental learning. This contingency-dependent temporal reorganization may support flexible adaptation of neural processing to changing reward contingencies during associative learning.
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